Lili C. Kudo

1.8k total citations
21 papers, 1.1k citations indexed

About

Lili C. Kudo is a scholar working on Molecular Biology, Cell Biology and Biomedical Engineering. According to data from OpenAlex, Lili C. Kudo has authored 21 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 3 papers in Cell Biology and 3 papers in Biomedical Engineering. Recurrent topics in Lili C. Kudo's work include Mitochondrial Function and Pathology (3 papers), Bioinformatics and Genomic Networks (3 papers) and Gene expression and cancer classification (3 papers). Lili C. Kudo is often cited by papers focused on Mitochondrial Function and Pathology (3 papers), Bioinformatics and Genomic Networks (3 papers) and Gene expression and cancer classification (3 papers). Lili C. Kudo collaborates with scholars based in United States, Japan and France. Lili C. Kudo's co-authors include Daniel H. Geschwind, Stanislav L. Karsten, Sarah E. London, Stephanie A. White, Ikuko Teramitsu, Todd M. Preuss, Carrolee Barlow, Matthew A. Zapala, Mario Cáceres and Joël Lachuer and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and PLoS ONE.

In The Last Decade

Lili C. Kudo

21 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Lili C. Kudo United States 13 607 238 158 138 107 21 1.1k
Mark Eddison United States 15 696 1.1× 106 0.4× 62 0.4× 365 2.6× 28 0.3× 24 1.3k
José Luis Ferrán Spain 24 816 1.3× 156 0.7× 75 0.5× 367 2.7× 30 0.3× 50 1.3k
Bradley M. Colquitt United States 9 427 0.7× 109 0.5× 303 1.9× 400 2.9× 49 0.5× 11 1.2k
Berta Alsina Spain 22 867 1.4× 108 0.5× 41 0.3× 321 2.3× 64 0.6× 37 1.5k
Fu‐Chin Liu Taiwan 18 591 1.0× 209 0.9× 52 0.3× 326 2.4× 28 0.3× 33 1.0k
Linda Vician United States 22 524 0.9× 123 0.5× 99 0.6× 370 2.7× 28 0.3× 32 1.3k
Nicolas Grillet United States 19 801 1.3× 72 0.3× 237 1.5× 131 0.9× 22 0.2× 28 1.5k
Thomas O. Fox United States 23 447 0.7× 465 2.0× 76 0.5× 180 1.3× 43 0.4× 41 1.4k
Kathy Kampf United States 21 828 1.4× 548 2.3× 52 0.3× 372 2.7× 96 0.9× 34 1.8k
Fernando García‐Moreno Spain 19 759 1.3× 125 0.5× 100 0.6× 480 3.5× 46 0.4× 33 1.7k

Countries citing papers authored by Lili C. Kudo

Since Specialization
Citations

This map shows the geographic impact of Lili C. Kudo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lili C. Kudo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lili C. Kudo more than expected).

Fields of papers citing papers by Lili C. Kudo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lili C. Kudo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lili C. Kudo. The network helps show where Lili C. Kudo may publish in the future.

Co-authorship network of co-authors of Lili C. Kudo

This figure shows the co-authorship network connecting the top 25 collaborators of Lili C. Kudo. A scholar is included among the top collaborators of Lili C. Kudo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lili C. Kudo. Lili C. Kudo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Karsten, Stanislav L., et al.. (2020). Nanopin - a Mems Based Sensor for the Analysis of Single-Cell Mechanical Properties. Biophysical Journal. 118(3). 315a–315a. 1 indexed citations
3.
Karsten, Stanislav L., Momoko Kumemura, Laurent Jalabert, et al.. (2016). Direct electrical and mechanical characterization of in situ generated DNA between the tips of silicon nanotweezers (SNT). Lab on a Chip. 16(11). 2099–2107. 3 indexed citations
4.
Karsten, Stanislav L., Mehmet C. Tarhan, Lili C. Kudo, Dominique Collard, & Hiroyuki Fujita. (2015). Point-of-care (POC) devices by means of advanced MEMS. Talanta. 145. 55–59. 17 indexed citations
5.
Tippin, Brigette L., Amy Lin, Lili C. Kudo, et al.. (2014). Intestinal tumor suppression in ApcMin/+ mice by prostaglandin D2 receptor PTGDR. Cancer Medicine. 3(4). 1041–1051. 17 indexed citations
6.
Kudo, Lili C., Tony Fields, Nuraly K. Avliyakulov, et al.. (2012). Novel Cell and Tissue Acquisition System (CTAS): Microdissection of Live and Frozen Brain Tissues. PLoS ONE. 7(7). e41564–e41564. 11 indexed citations
7.
8.
Winden, Kellen D., Stanislav L. Karsten, Anatol Bragin, et al.. (2011). A Systems Level, Functional Genomics Analysis of Chronic Epilepsy. PLoS ONE. 6(6). e20763–e20763. 61 indexed citations
9.
Karsten, Stanislav L., Lili C. Kudo, & Anatol Bragin. (2011). Use of peripheral blood transcriptome biomarkers for epilepsy prediction. Neuroscience Letters. 497(3). 213–217. 12 indexed citations
10.
Kudo, Lili C., Guijie Ren, Maria Hui, et al.. (2011). Puromycin-sensitive aminopeptidase (PSA/NPEPPS) impedes development of neuropathology in hPSA/TAUP301L double-transgenic mice. Human Molecular Genetics. 20(9). 1820–1833. 37 indexed citations
11.
Kudo, Lili C., Justine Pomakian, Paul N. Valdmanis, et al.. (2010). Integrative gene–tissue microarray-based approach for identification of human disease biomarkers: application to amyotrophic lateral sclerosis. Human Molecular Genetics. 19(16). 3233–3253. 50 indexed citations
12.
Karsten, Stanislav L., et al.. (2010). Predicting epilepsy with peripheral blood transcriptome biomarkers during early latent period. The FASEB Journal. 24(S1). 1 indexed citations
13.
Karsten, Stanislav L., Lili C. Kudo, & Daniel H. Geschwind. (2008). Gene Expression Analysis of Neural Cells and Tissues Using DNA Microarrays. Current Protocols in Neuroscience. 45(1). Unit 4.28–Unit 4.28. 8 indexed citations
14.
Kudo, Lili C., et al.. (2008). 451: Effects of low birth weight on hippocampal development: Possible mechanism for obesity-associated Alzheimer disease. American Journal of Obstetrics and Gynecology. 199(6). S135–S135. 1 indexed citations
15.
Kudo, Lili C., et al.. (2006). Genetic Analysis of Anterior-Posterior Expression Gradients in the Developing Mammalian Forebrain. Cerebral Cortex. 17(9). 2108–2122. 23 indexed citations
16.
Karsten, Stanislav L., Lili C. Kudo, & Daniel H. Geschwind. (2004). Microarray Platforms: Introduction and Application to Neurobiology. International review of neurobiology. 60. 1–23. 2 indexed citations
17.
Hedlund, Eva, Stanislav L. Karsten, Lili C. Kudo, Daniel H. Geschwind, & Ellen M. Carpenter. (2004). Identification of a Hoxd10‐regulated transcriptional network and combinatorial interactions with Hoxa10 during spinal cord development. Journal of Neuroscience Research. 75(3). 307–319. 30 indexed citations
18.
Teramitsu, Ikuko, Lili C. Kudo, Sarah E. London, Daniel H. Geschwind, & Stephanie A. White. (2004). ParallelFoxP1andFoxP2Expression in Songbird and Human Brain Predicts Functional Interaction. Journal of Neuroscience. 24(13). 3152–3163. 242 indexed citations
19.
Karsten, Stanislav L., Lili C. Kudo, Robert L. Jackson, et al.. (2003). Global analysis of gene expression in neural progenitors reveals specific cell-cycle, signaling, and metabolic networks. Developmental Biology. 261(1). 165–182. 100 indexed citations
20.
Cáceres, Mario, Joël Lachuer, Matthew A. Zapala, et al.. (2003). Elevated gene expression levels distinguish human from non-human primate brains. Proceedings of the National Academy of Sciences. 100(22). 13030–13035. 371 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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